Introduction of Edge and Fog Computing :

Edge and Fog Computing research are at the forefront of revolutionizing how we process data and deliver services in the age of IoT (Internet of Things) and real-time applications. These paradigms extend computation and data storage closer to the data source, reducing latency and bandwidth usage.

Edge Device Management:

This subfield focuses on managing and orchestrating edgedevices efficiently. Researchers work on developing tools and frameworks for device discovery, configuration, and  monitoring in dynamic edge environments.

Edge and Fog Analytics:

Analytics at the edge and fog levels are crucial for real-time decision-making. Researchers explore algorithms and techniques for processing and analyzing data locally, enabling faster, insights and reduced data transfer overhead.

Security in Edge and Fog Computing:

Security is a paramount concern in edge and fog computing, where data is Often processed at the network's edge. Researchers invastigate secure data transmission, access control, and threat detection mechanismse to protect edge and fog resources.

Edge and Fog for IoT:

Edge and fog computing play a pivotal role in IoT ecosystems. Research in this area focuses on optimizing data processing, ensuring low latency communication, and enabling edge-driven IoT applications.

Resource Management and Orchestration:

Efficient resource management is vital to harness the potential of  edge and fog computing. Researchers develop resource allocation algorithms, workload distribution strategies, and dynamic orchestration solutions to ensure optemal utilization of computing resources.